COURSE SUMMARY
Course Title: 
Signal Processing for Business Applications
Course Code: 
19CCE338
Year Taught: 
2019
Type: 
Elective
Degree: 
Undergraduate (UG)
School: 
School of Engineering
Campus: 
Chennai
Coimbatore

Signal Processing for Business Applications is an elective course offered in the B. Tech. in Computer and Communication Engineering program at School of Engineering, Amrita Vishwa Vidyapeetham.

Pre Requisite(s): Nil

Objectives

  • To understand the functioning of financial markets and the behavior of financial time series
  • To provide an introduction to application of signal processing techniques for identifying and forecasting patterns in financial time series
  • To develop an understanding of the process for design of a profitable trading system

Course Outcomes

  • CO1: Able to understand the structure of financial markets and asset pricing, models
  • CO2: Able to analyze a financial time series and employ technical analysis to identify patterns in it
  • CO3: Able to employ filters for detection and analysis of business cycles
  • CO4: Able to design an adaptive filter based system for predicting financial time series

CO – PO Mapping

PO/PSO/CO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2
CO1 3 2 - - - - - - - - - 2 2 -
CO2 2 3 - - - - - - - - - 2 2 -
CO3 2 3 - - - - - - - - - 2 2 2
CO4 - 2 3 - - - - - - - - 2 2 2

Unit 1

Structure of financial markets-financial instruments-stock price models-asset returns-modern portfolio theorycapital asset pricing model-relative value and factor models -Trading terminology-long and short positions-cost of trading – backtesting-pairs trading and mean reversion-statistical arbitrage-trend following- trending in multiple frequencies.

Unit 2

Measuring business cycles- The Hodrick – Prescott filter – Baxter– King filter - Technical Analysis – Indicators –Oscillators- Signal to noise ratio - Sine wave indicator – Instantaneous trend line - Identifying market modes– Transform arithmetic – FIR – IIR - Removing lag - Adaptive moving averages - Ehlers filters.

Unit 3 

Measuring market spectra - optimum predictive filters - Adapting standard indicators- High frequency tradingDesigning profitable trading system.

Textbook(s)

  • Ali N. Akansu and Mustafa Torun, “A Primer for Financial Engineering: Financial Signal Processing and Electronic Trading”, Academic Press, 2015.
  • RamazanGencay, FarukSelcuk& Brandon Whitdly, “An Introduction to Wavelets and other filtering methods in Finance and Economics”, Academic Press, 2002.

Reference(s)

  • John F Ehlers, “Rocket Science for Traders: Digital Signal Processing Applications”, John Wiley 2001.
  • Jack Clark Francis, Richard W. Taylor, “Investments, Schaum’s Outlines”, Tata McGraw Hill, 2006.

Evaluation Pattern

Assessment Internal External
Periodical 1 (P1) 15 -
Periodical 2 (P2) 15 -
*Continuous Assessment (CA) 20 -
End Semester - 50
*CA – Can be Quizzes, Assignment, Projects, and Reports.